Contributor profile

Jennifer Stark

Data Engineer & Analyst SpareRoom

Biography

Jennifer is a Data Engineer and Analyst at SpareRoom (Flatshare Ltd) and a co-organiser of the Manchester chapter of PyData (@pydatamcr).

Jennifer was a Research Scientist in the Computational Journalism Lab headed by Nicholas Diakopoulos at the University of Maryland, Merrill College of Journalism. Her work there involved examining algorithmic accountability and transparency including the use of algorithms in news media, and how they are researched and reported; data visualization; and developing automation and other tools for the newsroom or the news-consumer. She has presented her work at various journalism conferences including Computation & Journalism 2016, European Data and Computational Journalism 2017, and was a keynote speaker at Coda.Br 2017 in Brazil.

Jennifer came to the USA for a Neuroscience postdoctoral research position in a neuroimaging lab at the NIH in Baltimore. She earned her Ph.D. in Neuroscience from the University of Manchester, UK, her Master’s in Information Visualization from the Maryland Institute College of Art in Baltimore, USA, and a Certificate in Data Science from General Assembly in DC.

Content by Jennifer

Best practices Coding
Editorial transparency in computational journalism

As computational methods become more prevalent in the newsroom, Jennifer A. Stark examines the standards and expectations for ensuring editorial transparency.